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https://issues.apache.org/jira/browse/DRILL-5846?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16299574#comment-16299574
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ASF GitHub Bot commented on DRILL-5846:
---------------------------------------
Github user paul-rogers commented on a diff in the pull request:
https://github.com/apache/drill/pull/1060#discussion_r158196570
--- Diff: exec/vector/src/main/codegen/templates/NullableValueVectors.java
---
@@ -68,96 +85,441 @@
private final UInt1Vector bits = new UInt1Vector(bitsField, allocator);
private final ${valuesName} values = new ${minor.class}Vector(field,
allocator);
+ private final Mutator mutator = new MutatorImpl();
+ private final Accessor accessor = new AccessorImpl();
+
+ <#if type.major == "VarLen" && minor.class == "VarChar">
+ private final Mutator dupMutator = new DupValsOnlyMutator();
+ /** Accessor instance for duplicate values vector */
+ private final Accessor dupAccessor = new DupValsOnlyAccessor();
+ /** Optimization for cases where all values are identical */
+ private boolean duplicateValuesOnly;
+ /** logical number of values */
+ private int logicalNumValues;
+ /** logical value capacity */
+ private int logicalValueCapacity;
--- End diff --
Explain this? If I have `"foo.csv"` as my value (for `filename`, say) what
does it mean to have a "capacity"? Can't I have 64K "copies" of my one value?
> Improve Parquet Reader Performance for Flat Data types
> -------------------------------------------------------
>
> Key: DRILL-5846
> URL: https://issues.apache.org/jira/browse/DRILL-5846
> Project: Apache Drill
> Issue Type: Improvement
> Components: Storage - Parquet
> Affects Versions: 1.11.0
> Reporter: salim achouche
> Assignee: salim achouche
> Labels: performance
> Fix For: 1.13.0
>
>
> The Parquet Reader is a key use-case for Drill. This JIRA is an attempt to
> further improve the Parquet Reader performance as several users reported that
> Parquet parsing represents the lion share of the overall query execution. It
> tracks Flat Data types only as Nested DTs might involve functional and
> processing enhancements (e.g., a nested column can be seen as a Document;
> user might want to perform operations scoped at the document level that is no
> need to span all rows). Another JIRA will be created to handle the nested
> columns use-case.
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